A different bandwagon

I've been experimenting today with Second Life, Linden Labs' virtual reality environment. The environment is socially-oriented and derives much of its value from user generated content through scriptable objects that users can gift or sell through an in-game economy (although 'game' is a bit of a misnomer). There was news recently of Second Life's first virtual real-estate millionaire.

Various 'first life' businesses have also begun to make the move into Second Life: IBM have, for some time, had a dedicated set of Islands for their own use, which they've recently opened up to the public (see picture). Reuters have opened up a bureau dedicated to Second Life news, and Harvard Law School recently ran real classes in the environment.

The key to the success of Second Life is it's social aspect. Think of it as the next evolution of IRC, instant messaging, and collaboration software, rather than a game. This collaborative aspect may hold some possibilities for business intelligence. Academic and consultant Richard Hackathorn argues that Second Life holds some interesting possibilities for data visualisation. While true, I don't think that a "forest of data" is really the main benefit that this kind of environment can deliver. Rather, it's the collaborative aspect, the ability to meet in a virtual environment that relaxes the real-world laws of physics, the ability to share information in a new way that will deliver any benefits that might accrue. Assuming the technical hurdles are overcome, it may be one more way in which creative decisions can be supported.

Strategy and Russell Ackoff: One More Time

I promise this is the last post I will do for a while talking about Russell Ackoff, but I thought this was too good to ignore. I was browsing Tom Peters' blog when I came across this entry. In his post, as well as other places, Tom criticises strategic planning as a useful business activity. To back this up, he quotes Ackoff as cited by Henry Mintzberg in his book The Rise and Fall of Strategic Planning:

Recently I asked three corporate executives what decisions they had made in the last year that would not have been made were it not for their corporate plans. All had difficulty identifying one such decision. Since all of the plans are marked 'secret' or 'confidential,' I asked them how their competitors might benefit from possession of their plans. Each answered with embarrassment that their competitors would not benefit.

Imagine if the same question was asked in relation to some of the latest BI tools - especially executive dashboards. I wonder how many senior executives with a dashboard available to them made a decision that would have been different if they didn't have access to it? What would be the outcome if their competitors managed to get a glance at it? I suspect that the reactions would not be too dissimilar to Ackoff's questions, unfortunately...

New Blog Links

I've added links to two new blogs in the sidebar - Stephen Few's Visual Business Intelligence and Andrew Vande Moere's Information Aesthetics, both worth reading.

And speaking of Russell Ackoff...

He's got a new book out called Management f-LAWS. As the name suggests, the book is about how management really works, rather than some idealised view of managerial utopia. Essentially a set of management homilies based on Ackoff's insights from decades of observation, the freely downloadable part of the book ranges from the interesting ("Managers who don't know how to measure what they want settle for wanting what they can measure") to the whimsically silly ("The legibility of a male manager's handwriting is in inverse proportion to his seniority"). Perhaps a useful book for BI professionals, but look for the commentary from Sally Bibb on each of the 'f-LAWS' for the real value.

Repeating History

I've been tidying up some of my things in my office and came across an old paper I used as a reference when I was writing my honours thesis back in 1996. The paper[1], written by Elizabeth O'Sullivan back in 1985, was talking about decision support systems (DSS) and contrasted them with the management information systems (MIS) of the 1960s and 70s.

A bit of history first.

MIS, in the 1960s were a disastrous failure. They were developed with the mindset that a techno-centric approach to management was the optimal means of making decisions. They collated data from transaction processing systems, and churned out reports on a regular basis (paper-based, since managers didn't have terminals on their desktops). The systems were designed to support the decision-making needs of all managers in an organisation. Developers at the time argued things like:

With so useful information captured ... we have attempted to make this as freely available as possible to sections of management that can use the information effectively. Past approaches, where special one time programs written by the Systems Department programmers (if they could get time) ...

This appeared in a paper describing the Ford Motor Co.'s MIS approach in 1967. Sound familiar? It should. All of the things people were trying to achieve with MIS are the things they're trying to achieve now with BI and Data Warehousing. And it didn't work. Millions of dollars were spent and lost, and IT departments garnered a reputation that made business people question their hygiene, parentage and mental capacity.

You might be thinking that these systems failed because they were working with machines that boasted a whopping 32kb of memory, and 8mb of disk storage, and reported using paper-based printouts. In fact, the reasons they failed had nothing to do with the technology or its limitations. This is from a paper by Russell Ackoff, again, writing in 1967:

MIS are based on the following false assumptions:

• More information is better
• Managers don’t have the information they need
• Managers need the information they want
• Managers don’t have to understand a system to use it

None of these have anything directly to do with the technology used. In other words, MIS failed because the developers didn't understand managers, the way they work, and the way they make decisions. The same mindset is still surprisingly common with BI.

Back to the paper I found. Here's an extract from the opening paragraphs:

[DSS] represent an attitude that management information systems (MIS) can and should do more than serve routine organizational operations... To support decision making effectively, a DSS must be flexible, user friendly, and interactive. It should go beyond traditional MIS, ... [it] must recognize and accomodate individual problem-solving styles...

[Emphasis is mine]

DSS were phenomenally successful at the time in comparison to MIS. The reason for this is the attention paid to individual decision-support. The same holds true for BI today. There is no way BI will work unless developers understand decision-making as a human process, and pay attention to helping individual decision-makers with tailored support. Unfortunately, this attitude, prevalent in the 1980s DSS movement and key to its success, appears to be missing from today's vendors, and the majority of developers.

[1] O'SULLIVAN, E. (1985) Decision Support Systems: An Introduction for Program Evaluators. Evaluation Review, 9(1), 84-92. (unfortunately, not available online).

SQL Server to run 270TB Multi-node Data Warehouse

Computerworld are reporting that Microsoft are working on a massive data warehousing project for an external client, in an obvious aim to dispel the idea that SQL Server is a lightweight platform. From the article:

At the annual conference of the Professional Association for SQL Server (PASS) user group, Microsoft said it is designing a 270TB multinode data warehouse for a foreign (ie. non-US) government that it declined to identify. The software vendor is also working on a 162TB single-node installation for its own marketing department.

Of course, this doesn't explain how Microsoft are doing this (any tweaks under the hood?), or whether the warehouse itself will be of any use (no metrics on reporting, data mining, etc. throughput - and we all know how Microsoft are on benchmarking *wink*). Still, I quite like SQL Server (and the MS BI tool suite) as a product, and it has singlehandedly been responsible for the biggest shakeup in the BI industry in the past several decades (a much needed one at that). If this kind of data volume can be handled well by SQL Server 2005, as configured by your average corporate DBA, then Oracle and IBM are really going to be looking over their shoulders.

Criticising Edward Tufte

I'm a huge fan of Edward Tufte, and so are many people who are interested in the graphical presentation of information. He's got a lot of good things to say that BI people should listen to, and he says it in an engaging way. Pictured, right, is Minard's diagram of Napoleon's march on Moscow, used by Tufte as an exemplar of good graphical information presentation.

As with any guru, though, his adherents sometimes get bogged down with the minutae of what he says, rather than the underlying principles he tries to communicate. There's an interesting couple of posts over at Emergent Chaos in response to a criticism of the Minard diagram as a communication tool, and Juice Analytic's follow-up. The original criticism was made by Seth Godin in the following video:

Uncertain about uncertainty

One of the key theories that informs our teaching and research into BI at Monash comes from cognitive science. It states that, for a whole variety of reasons, people don't make rational decisions. Instead, we're subject to so-called cognitive biases. One category of bias has to do with how we think about statistics - as a rule, people are terrible at thinking in ways that are consistent with the laws of Bayesian probability. This is a real problem for BI developers, since most BI tools deal with quantitative values, and hence, statistics and probability. Even worse, just about everyone is subject to these biases, even trained mathematicians, and presumably, BI professionals.

I've just finished watching an excellent talk by statistician Peter Donnelly that covers this issue brilliantly. It's one of the recent TED podcast episodes, that I've referred to before, and runs for about 20 minutes.



If you want to find out more about some of the other (really freaky) cognitive biases that exist, check out our bias page at http://olap.sims.monash.edu.au/research/decision.nsf.

Father of BI? Is he having a laugh?!

Computer World are running a story on Howard Dresner, the former Gartner analyst who lays claim to having invented the phrase 'business intelligence'. From the article:

Howard Dresner coined the term "business intelligence" in 1989 while an analyst at research firm Gartner Inc. ... Dresner was seeking a term that would elevate the debate and better define the analysis of quantitative information by a wide variety of users.

I'm sorry, but at best, Dresner re-appropriated the term to rebadge what was then called DSS. H.P. Luhn actually invented the term, not in 1989, but in 1958 in an IBM Journal article called A Business Intelligence System, (vol. 2, no. 4, p.314) that pretty accurately predicts BI systems today. Here's the original definition of Business Intelligence from 1958 (Luhn, 1958, p. 314):

In this paper, business is a collection of activities carried on for whatever purpose, be it science, technology, commerce, industry, law, government, defense, et cetera. The communication facility serving the conduct of a business (in the broad sense) may be referred to as an intelligence system. The notion of intelligence is also defined here, in a more general sense, as "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

Sods to Howard Dresner and Gartner for claiming to have invented something they didn't, and to the Computer World people for not doing their research. It's interesting to see that Dresner is now redefining BI as "business process management" (from the CW article), something that's a bit removed from the aims of DSS and EIS, and from the sounds of it, Luhn's original definition too.

IBM and Business Objects form Strategic Global Alliance

Good news for those companies with both platforms - two of the largest software vendors, Business Objects (BO) and IBM have just announced a global strategic alliance. So what does this mean? The word is that the new agreement will provide enhanced support for those companies with both bits of software. What the agreement really means is that it will put BO and IBM in the position to capture even greater market share.
Read more...

Defining Business Intelligence

As academics, we are often working with concepts and ideas, and when we are researching these concepts, we need to have explicit definitions that specify what is, and what isn't, of interest to the study. Sometimes, as with the case of Business Intelligence, there is a fairly strong, but implicit, definition used in industry, which is fine, since an explicit definition beyond a specific project doesn't really matter too much.
However, for academics, this can create difficulties. Without an accepted explicit definition, particularly for a hot-topic like BI, academics jump on the bandwagon claiming the area as part of their expertise without justification. Recently we've been working with some academics from the harder end of the IT spectrum, and we've struggled to make the point that the 'intelligence' bit of BI is not the same as the 'intelligence' bit of AI, or even human intelligence, but rather in the sense that Herbert Simon used it: ie. monitoring and gathering information to support decision-making.

But even that doesn't really solve much. Some people view BI as just the hardware and software tools that support that process. Others see the process itself as BI: Ralph Kimball, for example, famously uses a publishing metaphor in relation to data warehousing. Some see BI as the delivery layer or front-end, and treat data warehouses as something quite separate. Others would include the whole information supply-chain as BI.

So, what is BI to you? Is it any technology that supports organisational decision making? Is it specifically reporting and analytics? Does this include enterprise reporting, or does BI go beyond a kind of passive, push technology? Does BI extend beyond supporting decision-making to the actions that result from a decision? What about operational versus strategic decisions?

Leave a comment and let us know.

Excel Core Knowledge Wiki

I was just browsing the excellent Juice Analytics blog, where I read a post talking about the creation of a wiki discussing the basic core skills needed to use Excel for data analysis. Surf on over to the Excel Core Knowledge Wiki, learn some things, and perhaps contribute!

Nicholas Carr at it again.

Former executive editor of Harvard Business Review, business writer, speaker, and unfailing trouble maker, Nicholas Carr is at it again. Carr, author famous (or should I say infamous) for his 2003 HBR article "IT Doesn't Matter" appears poised to stir fresh controversy in the IT industry, warning organizations to stop spending on technology. Read more.

BI Doesn't Matter?

As Marcus has pointed out, Nicholas Carr is at it again, as reported on ZDNet.com. I agree with Marcus' assessment over at 401 Percent that there are some holes in Carr's original article, but I tend to agree with his main point as reported in the ZDNet article: many companies spend too much on technology in the hope of a silver bullet, without considering alternative, even low-tech ways of achieving the same end. In the ZDNet article, Bob McDowell of Microsoft was quoted as saying "There was over-hype in the 90s and there was overspend... [we're] still paying the price now." The problem is, McDowell's assessment is too limited - the IT industry is still making the same mistake, driven by vendor marketing departments that oversell their product, whilst under-delivering. Nowhere is this more evident than in the BI sector.

Time and again I go to vendor presentations and seminars, and the sales pitch is the same: buy our product, and all of the analytic and reporting (read decision-making) needs of your organisation will be solved. Let us tell you about our volume licensing arrangements!

The problem is, few of these products solve any of the really thorny decision-making needs of organisations - especially highly strategic, novel, 'wicked' decision problems that require creative, lateral thinking for their resolution. The needs of decision-makers facing these problems are wide, varied and don't submit to the usual requirements elicitation techniques used during system analysis and design. The tricky part about supporting these needs is not the technology - it's understanding the human aspects of decision-making, including their limitations.

Carr's central point, that companies spend money on IT for a strategic advantage that isn't there, holds for BI too. Maybe, rather than forking out for the new, you-beaut dashboard addon in the latest version of a reporting tool, a manager would be better served by spending that money on some people to help with the decision process. Imagine, instead of spending millions on a BI package, an organisation spending that money on the salaries of a flying-squad of decision/business analysts, skilled in using IT as well as in strategic decision making - a kind of internal consulting company, able to build personalised decision support tools for individual decision-makers.

As an IT person, Carr's attitude bothers me, but that doesn't mean the bugger is wrong. Maybe BI folk should be arguing, too, for organisations to spend less on BI technology, and more on people who know how to get the most out of what's already there.

Another BI Blog

Just came across another, more established BI Blog called Bounded Rationality, by Mark Madsen. Bit more technically focused than us, and has some interesting things to say about the industry. I particularly like this post on some of the overblown claims some of the vendors put out there.

The inmates and the asylum.

Listening to your customers (or end-users) is a must for BI systems, or any system for that matter, right? If the users tell you they want a feature you should give it to them - and quickly if possible. Well, no. We often talk in our lectures that the role of an analyst in a decision support setting should be - what we call - an active one. The analyst shouldn't just be a passive interpreter of the user's requirements, translating everything the user's ask for into system designs. They need to take into account what the user community wants, but every now and again they need to intervene and change something. They might need to explain a better way of doing things, or explain that what the users are asking for is silly is somehow or another. All this takes great skill and care not to seem like a typical know it all IT person.

Here is an unusual example of taking what your user community wants too far - and sadly this is going to have a major impact on just about everybody working in BI. There is a feature in the upcoming version of Excel that is just plain wrong.

Microsoft has gone out of its way with its next release of office to take usability seriously. They have tried to embark on a brave remake of the product set. One of the potentially great new features they are including in Excel is the ability to quickly create bar charts that sit (ala Tufte's sparklines) in the spreadsheet cells, next to the numbers and text, not as a separate chart object. Great idea. However, the feedback they got from focus groups is that users don't like the look of these charts when one of the cells is 0 or very low compared to the others, so they have adjusted the bars displayed so there is a minimum that shows even when the quantity is 0. Oh dear. For some example charts and a discussion visit the (excellent) blog at Juice Analytics.

The Pros and Cons of Choice

This is perhaps not really appropriate as the first substantive post on this blog, given that it's not really about the technology of BI, but thought I'd post it anyway, as I'll forget if I don't do it now. I've been recently getting into some video podcasts from the TED conferences (Technology, Entertainment and Design). One recent episode was a presentation by Malcom Gladwell (author of Tipping Point) whose main theme was the importance of choice - that is, freedom to choose is closely tied to happiness.



Another, more recent episode, was a presentation by Barry Schwartz (author of The Paradox of Choice) whose point was that too much choice can have a number of strongly negative side-effects. In short, too much choice, amongst other things, leads to paralysis and post-decision regret of various kinds.



So why is this relevant to BI? BI systems are developed to help managers make decisions, and by providing them with information, we increase the number of choices available to decision-makers. Schwartz's point, though, would indicate that a naive approach to this is unproductive: simply plugging a manager into a data warehouse isn't going to help them make better decisions. In fact, it may actually make them worse decision makers.

I don't think too many people would disagree that a good BI tool doesn't give managers more information (well, it might, but not as a primary design aim), it helps managers to understand information to be able to make a better decision. BI systems are there to help provide a supportive decision making environment, and do so by adding 'structure' to the decision problem: that is, they help decision makers to focus on important information, while helping to filter out less important (but maybe still relevant) noise. Mark Silver calls this 'decisional guidance'. On the other hand, though, is still the need to allow the decision maker to make a real, free, and often unanticipated, choice.

My point is this: as BI developers, we need to balance the needs of the decision maker to make a free choice, while not overwhelming them with potentially choice-enabling information. BI isn't about building and deploying a data warehouse and an analytic tool suite. It's fundamentally about providing decision support, and sometimes that means restricting choice, rather than enabling it. Getting that balance right, of course, is often easier said than done, and raises all sorts of ethical issues.

Check out the videos, or subscribe to the podcast, at the TED Blog. I suggest watching the Malcolm Gladwell one first, followed by the Barry Schwartz video.

Welcome to the Monash BI Blog

This blog has been set up as another way in which the academics at the Monash Centre for Decision Support and Enterprise Systems Research can stay in touch with the Business Intelligence community. Members of the Centre interested in decision support have a long history in the area, going back to the 1970s. Our research is independent of vendors and consulting companies, and focussed on all aspects of using IT to support management decision making.

Whilst there are a number of BI blogs out there at the moment, most of them are written from a vendor or consultant perspective, and usually have a commercial slant to them. This blog will be written independent of a commercial imperative, and hopefully will be the base for a community of BI practitioners and researchers to share ideas and comments.